Forecasting innovations: Methods for predicting numbers of patent filings

Forecasting Innovations: Methods for Predicting Numbers of Patent Filings

Volumn , Issue , 2006, Pages 1-267

  Hingley, Peter ^a   Nicolas, Marc ^a  

^a EUROPEAN PATENT OFFICE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84890205043     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/3-540-35992-3     Document Type: Book

References (154)

1. Abbott A (2006) Rumblings from the fringe. Nature 439:910-911
2. Adbih Y, Joutz F (2005) Relating the knowledge production function to total factor productivity: an endogenous growth puzzle. International Monetary Fund Working Paper No WP/05/74
3. Aldrich JH, Nelson FD (1984) Linear probability, logit, and probit models. Sage, London
4. Armstrong JS (ed) (2001) Principles ofForecasting. Kluwer, Boston
5. Arellano M, Bond S (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58:277-297
6. Arellano M, Bover O (1995) Another look at the instrumental variable estimation of error-components models. Journal of Econometrics 68:29-51
7. Bainbridge D (1992) Intellectual property. Pitman, London
8. Baltagi B (2001) Econometric analysis of panel data, 2nd edn. Wiley, New York
9. Bertin G, Wyatt S (1988) Multinationals and Industrial Property. Harvester-Wheatsheaf, UK/Humanities Press, US
10. Blind K. (2004) The economics of standards: theory, evidence, policy. Edward Elgar, Cheltenham
11. Blind K, Grupp H (2000) Gesamtwirtschaftlicher Nutzen der Normung, Volks-wirtschaftlicher Nutzen: Zusammenhang zwischen Normung und technischem Wandel, ihr Einfluss auf die Gesamtwirtschaft und den AuBenhandel der Bundesrepublik Deutschland. German Institute for Standardisation (Deut-schen Institut fur Normung) (ed), Berlin
12. Blind K, Edler J, Frietsch R, Schmoch U (2003a) Erfindungen kontra Patente. Schwerpunktstudie "Zur technologischen Leistungsfahikeit Deutschlands", Fraunhofer Institute for Systems and Innovation Research, Karlsruhe
13. Blind K, Edler J, Schmoch U, Andersen B, Howells J, Miles I, Roberts J, Hipp C, Green L, Herstatt C, Evangelista R (2003b) Patents in the service industries. Final report, European Commission (ed), Brussels
14. Blind K, Edler J, Frietsch R, Schmoch U (2004) The patent upsurge in Germany: the outcome of a multi-motive game induced by large companies. Working paper presented at the 8th Schumpeter Conference in Milano, Fraunhofer Institute for Systems and Innovation Research, Karlsruhe
15. Blundell, R., Bond, S (1998) Initial conditions and moment restrictions in dynamic panel data models. Journal ofEconometrics 87:115-143
16. Bosworth DL (1984) Foreign patent flows to and from the United Kingdom. Re-searchPolicy 13:115-124
17. Bosworth DL (1980) The transfer of US technology abroad. Research Policy 9: 378-388
18. Box GEP, Jenkins GM (1976) Time series analysis forecasting and control. Hol-den-Day, San Francisco
19. Brockwell P, Davis R (1986) Time series: theory and methods. Springer Series in Statistics. Springer, Heidelberg
20. Brockwell P, Davis R (1996) Introduction to time series and forecasting. Springer Texts in Statistics. Springer, Heidelberg
21. Clements MP, Hendry, DF (1999) Forecasting non-stationary economic time series. MIT Press, Cambridge. MA
22. Cochran WG (1977) Sampling methods. Wiley, New York
23. Cohen W, Nelson R, Walsh J (1996) Appropriability conditions and why firms patent and why they do not in the American manufacturing sector. OECD Working Paper
24. Conover WJ (1999) Practical nonparametric statistics. Wiley, New York
25. Crepon B, Duguet E (1997) Estimating the innovative function from patent numbers: GMM on count panel data. Journal of Applied Econometrics 12:243263
26. Crepon B, Duguet E, Mairesse J (1998) Research, innovation and productivity: an econometric analysis at the firm level. Economics of Innovation and New Technology 7:115-158
27. Dangerfield BJ, Morris JS (1992) Top-down or bottom-up: aggregate versus disaggregate extrapolations. International Journal ofForecasting 8:233-241
28. Davison AC (2003) Statistical models. Cambridge
29. Dernis H, Khan M (2004) Triadic patent families methodology. OECD Directorate for science, technology and industry working paper 2004/2. Available at
30. Diebold FX, Lutz K (2000) Unit root tests are useful for selecting forecasting models. Journal of Business andEconomic Statistics 18: 265-273
31. DTI (2001) (Department of Trade and Industry) The 2001 R&D scoreboard: Company data. DTI, London. Available at http://www. innovation. gov. uk/ rdscoreboard/
32. Draper NR, Smith H (1981) Applied Regression Analysis. Wiley, New York
33. Durbin J, Koopman SJ (2001) Time series analysis by state space methods. Oxford
34. Eaton J, Kortum S (1996) Trade in ideas: patenting and productivity in the OECD. Journal oflnternational Economics 40:251-278
35. Engle R, Granger CWJ (1987) Co integration and error-correction: representation, estimation and testing. Econometrica 55:251-276
36. Ericsson NR, Irons JS (1994) (eds. ) Testing exogeneity.
37. Oxford EPIP (2003) (European Policy for Intellectual Property) First conference in Munich. Available at http://www. inno-tec. bwl. uni-muenchen. de/epip/index. html
38. EPIP (2005) (European Policy for Intellectual Property) EPIP welcome page. Available at http://www. dauphine. fr/imri/EPIP/welcome. html
39. Epoline (2006) (European Patent Office epoline website) Available at http:// www. epoline. org/portal/public
40. EPO (2006) (European Patent Office) Applicant panel surveys of intentions for filing patent applications at the European Patent Office and other Offices. Survey reports for annual surveys from 2001 to 2005. Authors:
41. Andersen S, Hingley P (2001, 2002, 2003 surveys), European Patent Office with Roland Berger Market Research (2004, 2005 surveys). Available at http://www. european-patent-office. org/aps/
42. EPO (1994) (European Patent Office) Utilisation of patent protection in Europe. Eposcript 3, European Patent Office, Munich
43. EPO (2002) (European Patent Office) European Patent Convention, 11th edn. Available at: http://www. european-patent-office. org/epc/pdf-e. htm
44. EPO (2003) (European Patent Office) European Union, Community Patent-Common political approach of 3 March 2003. Notice from the European Patent Office. Available at http://www. european-patent-office. org/news/info/ 2003-04-30-e. htm
45. EPO, JPO, USPTO (2005) (European Patent Office, Japan Patent Office, United States Patent and Trademark Office) Trilateral Statistical Report, 2004 edn. Available at http://www. trilateral. net/tsr/tsr-2004/
46. European Commission (2002) Summary report of replies to the questionnaire on the impact of the Community utility model with a view to updating the Green Paper on protection by the utility model in the internal market.
47. Document SEC(2001)1307, Available at http://europa. eu. int/comm/internal-market/ indprop/docs/model/utilreporten. pdf
48. European Commission (2006) Statistical classification of economic activities in the European Community, Rev 1. 1. Available at http://europa. eu. int/comm/ eurostat/ramon
49. Evenson R, Puttnam J (1988) The Yale-Canada patent flow concordance. Economic Growth Centre Working Paper, Yale University, New Haven
50. Fagerberg J (1988) International Competitiveness. Economic Journal 98:355-374
51. Favero CA (2001) Applied macroeconometrics. Oxford
52. Fildes R (1992) The evaluation of extrapolative forecasting methods (with discussion). International Journal ofForecasting 8:81-111
53. Fraunhofer-ISI (Fraunhofer Institute for Systems and Innovation Research), IWW, NIW, DIW, ZEW (2002) Germany's technological performance 2001. Federal Ministry of Education and Research (ed), Bonn
54. Funke M (1990) Assessing the forecasting accuracy of monthly vector autoregres-sive models: the case of five OECD countries. International Journal of Forecasting 6:363-378
55. Gardner ES Jr, McKenzie E (1988) Model identification in exponential smoothing. Journal of the Operational Research Society 39:863-867
56. Geroski P, Van Reenen J, Walters C (2002) Innovations, patents and cash flow. In: Kleinknecht A, Mohnen P (ed), Innovation and Firm Performance. Palm-grave Macmillan, Basingstoke, pp 31-55
57. Gibbons JD and Chakraborti S (2003) Nonparametric statistical inference. Chapman and Hall, London
58. Ginarte J, Park WG (1997) Determinants of patent rights: a cross-national study. ResearchPolicy 26:283-301
59. Giudici P (2003) Applied data mining. Wiley, Chichester
60. Greenhalgh C (1990) Innovation and trade performance in the UK. Economic Journal 100:105-118
61. Greif S, Potkowik G (1990) Patente and Wirtschaftszweige: Zusammenfiihrung der Internationalen Patentklassifikation and der Systematik der Wirtschaftszweige. Carl Heymann, Cologne
62. Griliches Z (1990) Patent statistics as economic indicators: a survey. Journal of Economic Literature 28:1661-1707
63. Grupp H, Jungmittag A, Schmoch U, Legler H (2000) Hochtechnologie 2000: Neudefinition der Hochtechnologie fur die Berichterstattung zur technologi-schen Leistungsfahigkeit Deutschlands. Fraunhofer Institute for Systems and Innovation Research, Karlsruhe
64. Grupp H, Munt G, Schmoch U. (1996) Assessing different types of patent data for describing high-technology export performance. In: Innovation, Patents and Technological Strategies, OECD (ed. ), Paris
65. Hall B, Jaffe AB, Trajtenberg M (2001) The NBER patent citation data file: lessons, insights and methodological tools. National Bureau of Economic Research Working Paper No 8498
66. Hall B, Ziedonis R (2001) The patent paradox revisited: an empirical study of patenting in the US semiconductor industry, 1979-1995. Rand Journal of Economics 32:101-128
67. Harhoff D, Scherer F, Vopel K (2003) Citations, family size, opposition and the value of patent rights. ResearchPolicy 32:1343-1363
68. Hausman J, Hall B, Griliches Z (1984) Econometric models for count data with an application to the patents R&D relationship. Econometrica 52:909-938
69. Hendry DF (1986) Using PC-GIVE in econometrics teaching. Oxford Bulletin of Economics and Statistics, 48:87-98
70. Hendry DF (1993) Econometrics: alchemy or science? Blackwell, Oxford
71. Hendry DF (1995) Dynamic econometrics. Oxford
72. Hingley P (1997) The extent to which national research and development expenditures affect first patent filings in contracting states of the European Patent Convention. World Patentlnformation 19:15-25
73. Hingley P (2004) Analytic estimator densities for common parameters under mis-specified models. In: Hubert M, Pison G, Struyf A, Van Aelst S (eds) Theory and applications of recent robust methods. Statistics for Industry and Technology, Birkhauser, Basel
74. Hingley P (2006) Applications of a technique for estimator densities which allows for model misspecification. Computational Statistics and Data Analysis, submitted
75. Hingley P, Nicolas M (1999) Improvements to methods for forecasting patent applications using information on patent families. Unpublished paper presented to 19th International symposium on forecasting, Washington DC, 27-30 June 1999
76. Hingley P, Nicolas M (2004) Methods for forecasting numbers of patent applications at the European Patent Office. World Patent Information 26:191-204
77. Hingley P, Park WG (2003) Patent family data and statistics at the European Patent Office. WIPO-OECD workshop on statistics in the patent field. Geneva. Available at www. wipo. int/patent/meetings/2003/statistics- workshop/en/ presentation/statisticsworkshophingley. pdf
78. Hyndman RJ, Koehler AB, Snyder RD, Grose S (2002) A state space framework for automatic forecasting using exponential smoothing methods. International JournalofForecasting 18:439-454
79. Insightful (2002) S+FinMetrics. Insightful corporation, Seattle, Washington
80. Insightful (2001) S-PLUS 6 for Windows user's guide. Insightful Corporation, Seattle, Washington
81. Janz N, Licht G, Doherr T (2001) Innovation activities and European patenting of German firms: a panel data analysis. Paper presented at the Annual Conference of the European Association of Research in Industrial Economics / Working Paper, Centre for European Economic Research (ZEW), Mannheim
82. Johansen S (1988) Statistical analysis of cointegration vectors. Journal of Economic Control and Dynamics 12:231-54
83. Johnson D (2002) The OECD Technology Concordance (OTC) Patents by industry of Manufacturer and sector of use, STI working paper 2002/5, Paris OECD.
84. Joutz FL, Maxwell WF (2002) Modelling the yields on noninvestment grade bond indices: credit risk and macroeconomic factors. International Review of Fi-nancialAnalysis, 11:345-374
85. Jungmittag A, Blind K, Grupp H (1999) Innovation, standardization and the long-term production function: a co-integration approach for Germany. Zeitschrift fur Wirtschafts-und Sozialwissenschaften 119:205-222
86. Kalton G (1983) Introduction to survey sampling. Sage, London
87. Kish L (1995) Survey sampling. Wiley, New York
88. Kortum S, Lerner J (1997) Stronger protection or technological revolution: what is behind the recent surge in patenting? National Bureau of Economic Research Working Paper 6204, Cambridge MA
89. Kortum S, Lerner J. (1998) Does Venture Capital Spur Innovation? National Bureau ofEconomic Research Working Paper No 6846
90. Kortum S, Lerner J (1999) What is behind the recent surge in patenting? Research Policy28:l-22
91. Lanjouw JO, Schankerman M (1999) The quality of ideas: measuring innovation with multiple indicators. National Bureau of Economic Research Working Paper No 7345
92. Lanjouw JO, Pakes A, Putnam J (1998) How to count patents and value intellectual property: uses of patent renewal and application data. Journal of Industrial Economics 46:405-433
93. Lee ES, Forthofer RN, Lorimor RJ (1989) Analyzing complex survey data. Sage, London
94. Levin R, Klevorick A, Nelson R, Winter S (1987) Appropriating the returns from industrial research and development. Brookings Paper on Economic Activity 3:784-829
95. Li H, Maddala GS, Trost R, Joutz F (1997) Estimation of short run and long run elasticities of energy demand from panel data using shrinkage estimators. Journal ofBusiness and Economics Statistics, 15:
96. Liao TF (1994) Interpreting probability models. Logit, probit, and other generalized linear models. Sage, London
97. Lofstedt R (ed) (2003) Riskworld. Journal of Risk Research 6: Issues 4-6
98. Long JS (1997) Regression models for categorical and limited dependent variables. Sage, London
99. Lutkepohl H (1993) Introduction to multiple time series analysis, 2nd edn. Springer, Heidelberg
100. MacKichan Software (2006) Scientific Notebook. Available at http://www. mackichan. com
101. Maddala GS (2001) Econometrics, Wiley, Chichester
102. Maskus KE (2000) Intellectual property rights in the global economy. Institute for International Economics, Washington, DC
103. Meade N (2000) Evidence for the selection of forecasting methods. Journal of Forecasting 19:515-535
104. Microsoft (2006) Office Online: Excel, http://oftice. microsoft. com
105. Miller JR (1998) Spatial aggregation and regional economic forecasting. The Annals ofRegional Science 32:253-266
106. Mills TC (1999) The econometric modelling of financial time series. Cambridge University Press
107. Nelson CR, Plosser CI (1982) Trends and random walks in macroeconomic time series: some evidence and implications. Journal of Monetary Economics, 10:139-162
108. Nickell S (1981) Biases in dynamic models with fixed effects. Econometrica, 49:1417-1426
109. NiilerE(2003) SanDiego. Nature 426:690-694
110. OECD (2003) (Organization for Economic Cooperation and Development) Main science and technology indicators. OECD, Paris. Available from www. oecd. org
111. OECD (2005a) (Organization for Economic Cooperation and Development) Compendium of patent statistics 2005. Available at http://www. oecd. org/dataoecd/ 60/24/8208325. pdf
112. OECD (2005b) (Organisation for economic cooperation and development) Patent statistics task force. 2005 annual meeting summary. Available at http://www. oecd. org/dataoecd/48/24/33938582. pdf OECD (2005c) See OECD (2003)
113. OFR (2004a) (The Office of the Federal Register) Federal Register 69(31). National Archives and Records Administration, p 7454
114. OFR (2004b) (The Office of the Federal Register) Federal Register 69(149). National Archives and Records Administration, p 47123
115. Pakes A (1986) Patents as options: some estimates of the value of holding European patent stocks. Econometrica 54:755-784
116. Pampel FC (2000) Logistic regression: a primer. Sage, London
117. Pankratz A (1983) Forecasting with univariate Box-Jenkins models: concepts and cases. Wiley, New York
118. Park WG (2001) International patenting, patent rights, and technology gaps. Working Paper, Department of Economics, American University
119. Pastor L (2002) A model weighting game in estimating expected returns. In: Mastering investment, your single source guide to becoming a master of investment. J Pickford (ed), FT Prentice-Hall, Harlow, UK
120. Preez J du, Witt F (2003) Univariate versus multivariate time series forecasting: an application to international tourism demand. International Journal of Forecasting 19:435-451
121. Putnam J (1996) The value of international patent rights. PhD thesis, Yale University, New Haven, CT
122. Ramsay JO, Silverman BW (1997) Functional data analysis. Springer, Heidelberg
123. Rossana RJ, Seater JJ (1995) Temporal aggregation and economic time series. Journal ofBusiness andEconomic Statistics 13:441-451
124. Rutterford J (1983) Introduction to stock exchange investment. Macmillan, London
125. Sarndel CE, Swensson B, Wretman J (1992) Model assisted survey sampling. Springer, New York
126. SAS Inc (2006) Analytics. Available at http://www. sas. com/technologies/analytics /index. html
127. Schankerman M, Pakes A (1986) Estimates of the value of patent rights in European countries during the post-1950 period. Economic Journal 97:1-25
128. Schiffel D, Kitti C (1978) Rates of invention: international patent comparisons. Research Policy 7:324-340
129. Schmoch U, Laville F, Patel P, Frietsch R (2003) Linking technology areas to industrial sectors. Report to the European Commission, DG Research, Fraunhofer Institute for Systems and Innovation Research, Karlsruhe, Paris, Brighton
130. Schmoch U, Koschatzky K (1996) Freie Erfindungen erfolgreich verwerten. In: Grupp H (ed) Schriftenreihe Zukunft der Technik. TUV Rheinland, Cologne
131. Schwartzkopf AB, Tersine RJ, Morris JS (1998) Top-down versus bottom-up forecasting strategies. International Journal of Production Research 26:183318
132. Shumway R, Staffer D (1999) Time series analysis and its applications. Springer Texts in Statistics, Springer, Heidelberg
133. Slama J (1981) Analysis by means of a gravitation model of international flows of patent applications in the period 1967-1978. World Patent Information 3:1-8
134. Stock JH (1988) Estimating continuous-time processes subject to time deformation. Journal of the American Statistical Association 83:77-85
135. Swamy PAVB, Tavlas GS (2005) Theoretical conditions under which monetary policies are effective and practical obstacles to their verification. Economic Theory 25:999-1005
136. Tong H (1990) Nonlinear time series: a dynamical systems approach. Oxford University Press
137. UN (2006) (United Nations statistics division) ISIC Rev. 3. 1, detailed structure and explanatory notes. Available at http://unstats. un. org/unsd/cr/registry
138. UNESCO (1980-2002) (United Nations Educational, Scientific and Cultural Organisation) Statistical Yearbook (1980-2002). Paris
139. Verspagen B, Morgastel T v, Slabbers M (1994) MERIT concordance table: IPC-ISIC (rev. 2). MERIT ResearchMemorandum, Maastricht
140. Wakelin K (1997) Trade and innovation: theory and evidence. Edward Elgar, Cheltenham
141. Wei W (1990) Time series analysis. Addison-Wesley, New Jersey
142. Wilcox R (2005) Robust estimation and hypothesis testing. Elsevier, Burlington, MA
143. Woolridge JM (2002) Econometric analysis of cross section and panel data. MIT
144. Press, Cambridge, MA World Bank (2002) World development indicators.
145. Washington, DC WIPO (2000) (World Intellectual Property Organisation) International Patent Classification, guide, survey of classes and summary of main groups. 7th edn, vol 9. Geneva
146. WIPO (2003) (World Intellectual Property Organisation) Workshop on statistics in the patent field, session on Patents by industry, http://www. wipo. int/patent/ meetings/2003/statistics-workshop/en/program. htm
147. WIPO (2004) (World Intellectual Property Office) WIPO-OECD Workshop on the use of patent statistics, with the support of EPO, JPO and USPTO. Available at http://www. wipo. int/patent/meetings/2004/statistics-workshop/en/
148. WIPO (2005) (World Intellectual Property Organisation) International Patent Classification. Available at: http://www. wipo. int/classifications/ipc/ en/ preface. htm
149. WIPO (2006a) (World Intellectual Property Organization) Paris Convention for the Protection of Industrial Property, of March 20, 1883, as amended September 28, 1979. Available at http://www. wipo. int/treaties/en/ip/paris/pdf/ trt docs-wo020. pdf
150. WIPO (2006b) (World Intellectual Property Organisation) PCT Newsletter. Available at http://www. wipo. int/pct/en/newslett
151. Zellner A (1962) An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association 57:348-368
152. Zhao JX, Foulkes AS, George EI (2005) Exploratory Bayesian model selection for serial genetics data. Biometrics 61:591-599
153. Zhou H (2004) Forecasting PCT filings. Presented at WIPO-OECD Workshop on the use of patent statistics, with the support of EPO, JPO and USPTO. Available at http://www. wipo. int/patent/meetings/2004/statistics-workshop/en/ presentations/statisticsworkshopzhou. pdf
154. Zivot E, Wang J (2003) Modeling financial time series with S-PLUS. Insightful Corporation, Seattle